1 citations · 1 across the 3 of their papers we have counts for
4 papers
SPeaR: Test-Time Adaptation with Steering Primitives for Realigning Representations
Muhammad Sudipto Siam Dip, Ali Etemad
Test-time adaptation (TTA) addresses distribution shift using only unlabeled test data. Existing methods typically adapt pretrained models by updating their parameters, limiting bo…
Optimized Feature Selection and Neural Network-Based Classification of Motor Imagery Using EEG Signals
Muhammad Sudipto Siam Dip, Mohammod Abdul Motin, Md. Anik Hasan +1
Objective: Machine learning- and deep learning-based models have recently been employed in motor imagery intention classification from electroencephalogram (EEG) signals. Neverthel…
NeuroSleepNet: An Explainable Multi-Head Attention-Based Framework With Spatial and Multi-Scale Independent Temporal Context Learning for Automatic Sleep Stage Scoring
Muhammad Sudipto Siam Dip, Mohammod Abdul Motin, Chandan Karmakar +2
Automatic sleep stage scoring is crucial for monitoring sleep quality and sleep-related disorders. However, most existing electroencephalogram (EEG) based deep learning frameworks…
oboVox Far Field Speaker Recognition: A Novel Data Augmentation Approach with Pretrained Models
Muhammad Sudipto Siam Dip, Md Anik Hasan, Sapnil Sarker Bipro +2
In this study, we address the challenge of speaker recognition using a novel data augmentation technique of adding noise to enrollment files. This technique efficiently aligns the…